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Asymptotic Efficiency of Statistical Estimators: Concepts and Higher Order Asymptotic Efficiency: Concepts and Higher Order Asymptotic Efficiency
Akahira, Masafumi; Takeuchi, Kei
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Description for Asymptotic Efficiency of Statistical Estimators: Concepts and Higher Order Asymptotic Efficiency: Concepts and Higher Order Asymptotic Efficiency
paperback. Series: Lecture Notes in Statistics. Num Pages: 242 pages, biography. BIC Classification: PBW. Category: (G) General (US: Trade). Dimension: 229 x 152 x 14. Weight in Grams: 379.
This monograph is a collection of results recently obtained by the authors. Most of these have been published, while others are awaitlng publication. Our investigation has two main purposes. Firstly, we discuss higher order asymptotic efficiency of estimators in regular situa tions. In these situations it is known that the maximum likelihood estimator (MLE) is asymptotically efficient in some (not always specified) sense. However, there exists here a whole class of asymptotically efficient estimators which are thus asymptotically equivalent to the MLE. It is required to make finer distinctions among the estimators, by considering higher order terms in the expansions ... Read more
This monograph is a collection of results recently obtained by the authors. Most of these have been published, while others are awaitlng publication. Our investigation has two main purposes. Firstly, we discuss higher order asymptotic efficiency of estimators in regular situa tions. In these situations it is known that the maximum likelihood estimator (MLE) is asymptotically efficient in some (not always specified) sense. However, there exists here a whole class of asymptotically efficient estimators which are thus asymptotically equivalent to the MLE. It is required to make finer distinctions among the estimators, by considering higher order terms in the expansions ... Read more
Product Details
Format
Paperback
Publication date
1981
Publisher
Springer United States
Number of pages
242
Condition
New
Series
Lecture Notes in Statistics
Number of Pages
242
Place of Publication
New York, NY, United States
ISBN
9780387905761
SKU
V9780387905761
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